Preventing unintended proteolysis in plant protein biofactories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SUMMARY: Numerous reports have been published over the last decade assessing the potential of plants as useful hosts for the heterologous expression of clinically useful proteins. Significant progress has been made, in particular, in optimizing transgene transcription and translation in plants, and in elucidating the complex post-translational modifications of proteins typical of the plant cell machinery. In this article, we address the important issue of recombinant protein degradation in plant expression platforms, which directly impacts on the final yield, homogeneity and overall quality of the resulting protein product. Unlike several more stable and structurally less complex pharmaceuticals, recombinant proteins present a natural tendency to structural heterogeneity, resulting in part from the inherent instability of polypeptide chains expressed in heterologous environments. Proteolytic processing, notably, may dramatically alter the structural integrity and overall accumulation of recombinant proteins in plant expression systems, both in planta during expression and ex planta after extraction. In this article, we describe the current strategies proposed to minimize protein hydrolysis in plant protein factories, including organ-specific transgene expression, organelle-specific protein targeting, the grafting of stabilizing protein domains to labile proteins, protein secretion in natural fluids and the co-expression of companion protease inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it